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Optimal design study of high order FIR digital filters based on neural network algorithm 被引量:2
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作者 Wang Xiaohua & He YigangCollege of Electrical and Information Engineering, Hunan University, Changsha 410082, P. R. China College of Electrical and Information Engineering, Changsha University of Science and Technology,Changsha 410077, P. R. China 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2004年第2期115-119,130,共6页
An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amp... An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amplitude response of the desired FIR filter and that of the designed by training the weights of neural networks, then obtains the impulse response of FIR digital filter . The convergence theorem of the neural networks algorithm is presented and proved, and the optimal design method is introduced by designing four kinds of FIR digital filters , i.e., low-pass, high-pass, bandpass , and band-stop FIR digital filter. The results of the amplitude responses show that attenuation in stop-bands is more than 60 dB with no ripple and pulse existing in pass-bands, and cutoff frequency of passband and stop-band is easily controlled precisely .The presented optimal design approach of high order FIR digital filter is significantly effective. 展开更多
关键词 high order FIR digital filters amplitude-frequency response neural network convergence theorem optimal design.
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Design of twodimensional digital filters using neural networks 被引量:1
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作者 Wang Xiaohua He Yigang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2005年第4期767-771,共5页
A new approach for the design of two-dimensional (2-D) linear phase FIR digital filters based on a new neural networks algorithm (NNA) is provided. A compact expression for the transfer function of a 2-D linear ph... A new approach for the design of two-dimensional (2-D) linear phase FIR digital filters based on a new neural networks algorithm (NNA) is provided. A compact expression for the transfer function of a 2-D linear phase FIR filter is derived based on its frequency response characteristic, and the NNA, based on minimizing the square-error in the frequency-domain, is established according to the compact expression. To illustrate the stability of the NNA, the convergence theorem is presented and proved. Design examples are also given, and the results show that the ripple is considerably small in passband and stopband, and the NNA-based method is of powerful stability and requires quite little amount of computations. 展开更多
关键词 2-D linear-phase FIR digital filters neural network convergence theorem stability.
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Asymptotic and stable properties of general stochastic functional differential equations
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作者 Xiaojing Zhong Feiqi Deng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第1期138-143,共6页
The asymptotic and stable properties of general stochastic functional differential equations are investigated by the multiple Lyapunov function method, which admits non-negative up-per bounds for the stochastic deriva... The asymptotic and stable properties of general stochastic functional differential equations are investigated by the multiple Lyapunov function method, which admits non-negative up-per bounds for the stochastic derivatives of the Lyapunov functions, a theorem for asymptotic properties of the LaSal e-type described by limit sets of the solutions of the equations is obtained. Based on the asymptotic properties to the limit set, a theorem of asymptotic stability of the stochastic functional differential equations is also established, which enables us to construct the Lyapunov functions more easily in application. Particularly, the wel-known classical theorem on stochastic stability is a special case of our result, the operator LV is not required to be negative which is more general to fulfil and the stochastic perturbation plays an important role in it. These show clearly the improvement of the traditional method to find the Lyapunov functions. A numerical simulation example is given to il ustrate the usage of the method. 展开更多
关键词 stochastic functional differential equations Lyapunov functions LaSalle asymptotic properties STABILITY semi-martingale convergence theorem.
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Four optimal design approaches of high-order finite-impulse response filters based on neural network
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作者 王小华 何怡刚 刘美容 《Journal of Central South University of Technology》 EI 2007年第1期94-99,共6页
Four optimal approaches of high-order finite-impulse response(FIR) digital filters were developed for designing four types filters using neural network algorithms. The solutions were presented as parallel algorithms t... Four optimal approaches of high-order finite-impulse response(FIR) digital filters were developed for designing four types filters using neural network algorithms. The solutions were presented as parallel algorithms to approximate the desired frequency response specification. Therefore, these methods avoid matrix inversion, and make a fast calculation of the filter’s coefficients possible. The convergence theorems of these proposed algorithms were presented and proved to illustrate them stable, and the implementation of these methods was described together with some design guidelines. The simulation results show that the ripples of the designed FIR filters are significantly little in the pass-band and stop-band, and the proposed algorithms are of fast convergence. 展开更多
关键词 high-order finite-impulse response digital filter frequency response neural network convergence theorem
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